CN110031007B - Flight path planning method and device and computer readable storage medium - Google Patents
Flight path planning method and device and computer readable storage medium Download PDFInfo
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Abstract
The embodiment of the invention discloses a flight path planning method, a device and a computer readable storage medium, when planning the flight path of an aircraft, firstly carrying out three-dimensional modeling on a physical space when the aircraft is in flight, determining a starting point and an end point of the flight path to be planned in a three-dimensional space environment model, taking the starting point as an initial flight path planning node, then carrying out calculation on a flight path optimization coefficient f (o) and a distance d (o) from the end point on a detection point on a circumference which takes a preset path search distance as a radius and takes the flight path planning node as a circle center, analyzing the condition of obstacles between each detection point and the end point based on a calculation result, then replanning the flight path planning node to carry out the next round of path search until the end point is searched, and finally determining the planned flight path according to the starting point, the newly planned flight path planning node and the end point, the method effectively reduces the calculation amount of the flight path planning, improves the flight path generation efficiency, and reduces the deviation of the planned flight path.
Description
Technical Field
The present invention relates to the field of path planning technologies, and in particular, to a method and an apparatus for planning a flight path, and a computer-readable storage medium.
Background
In order for an aircraft to autonomously complete a mission in a dynamic environment, the flight path planning of the aircraft is an unimportant part. With the continuous expansion of the application scenes of the aircraft, the research value of the flight path planning of the aircraft is also continuously improved.
Specifically, the planning of the flight path of the aircraft refers to that the aircraft searches an optimal collision-free path from a starting point to an end point according to one or more preset performance indexes. At present, when planning a flight path, an a-algorithm and an artificial fish swarm algorithm are generally adopted, wherein the a-algorithm randomly searches for extended nodes in peripheral nodes of the a-algorithm, the artificial fish swarm algorithm randomly searches for the extended nodes within a certain range, the calculated amount of the a-algorithm and the extended nodes in the execution process of the a-algorithm and the artificial fish swarm algorithm is large, the efficiency of flight path generation is low, and the generated flight path has a certain deviation from the actual optimal flight path.
Disclosure of Invention
The embodiments of the present invention mainly aim to provide a method, an apparatus, and a computer-readable storage medium for planning a flight path, which can at least solve the problems that when a route planning is performed by using an a-algorithm and an artificial fish swarm algorithm in the related art, the efficiency of generating the flight path is low, and a certain deviation exists between the generated flight path and an actual optimal flight path.
In order to achieve the above object, a first aspect of the embodiments of the present invention provides a flight path planning method, including:
a, constructing a three-dimensional space environment model based on a physical space of an aircraft during navigation, and determining a starting point and an end point of a flight path to be planned on the three-dimensional space environment model; the starting point is an initial track planning node;
step B, taking a target point on a circumference formed by taking a track planning node as a circle center and a preset path searching distance as a radius as a track detection point, and calculating f (o) and d (o) of all the track detection points; wherein o is the mark of the track detection point, f (o) is the track optimization coefficient, f (o) is related to d (o) and m (o), m (o) is the barrier coefficient, when m (o) is 0, the path test point is characterized not to pass through the barrier, when m (o) is not equal to 0, the path test point is characterized to pass through the barrier, and d (o) is the straight line distance between the track detection point and the terminal point;
step C, when a target track detection point with f (o) equal to infinity and d (o) equal to 0 exists on the circumference, determining the target track detection point as the end point; when all the track detection points on the circumference do not meet f (o) is equal to infinity and d (o) is equal to 0, determining a newly planned track planning node and returning to execute the step B;
and D, after the end point is detected through the circumference, determining a planned flight path in the three-dimensional space environment model according to the starting point, the newly planned flight path planning node and the end point.
In order to achieve the above object, a second aspect of the embodiments of the present invention provides a flight path planning apparatus, including:
the model building module is used for building a three-dimensional space environment model based on a physical space of an aircraft during navigation and determining a starting point and an end point of a flight path to be planned on the three-dimensional space environment model; the starting point is an initial track planning node;
the calculation module is used for taking a target point on a circumference formed by taking a track planning node as a circle center and a preset path search distance as a radius as a track detection point and calculating f (o) and d (o) of all the track detection points; wherein o is the mark of the track detection point, f (o) is the track optimization coefficient, f (o) is related to d (o) and m (o), m (o) is the barrier coefficient, when m (o) is 0, the path test point is characterized not to pass through the barrier, when m (o) is not equal to 0, the path test point is characterized to pass through the barrier, and d (o) is the straight line distance between the track detection point and the terminal point;
a planning module for determining a target track detection point as the end point when the target track detection point of f (o) equal to ∞ and d (o) equal to 0 exists on the circumference; when all the track detection points on the circumference do not satisfy f (o) is equal to ∞ and d (o) is equal to 0, determining a newly planned track planning node and inputting the newly planned track planning node to the calculation module to cause the calculation module to continue to execute its function;
and the route determining module is used for determining a planned route in the three-dimensional space environment model according to the starting point, the newly planned route planning node and the end point after the end point is detected through the circumference.
To achieve the above object, a third aspect of embodiments of the present invention provides an electronic apparatus, including: a processor, a memory, and a communication bus;
the communication bus is used for realizing connection communication between the processor and the memory;
the processor is configured to execute one or more programs stored in the memory to implement the steps of any of the above-mentioned flight path planning methods.
To achieve the above object, a fourth aspect of the embodiments of the present invention provides a computer-readable storage medium storing one or more programs, which are executable by one or more processors to implement the steps of any one of the above-mentioned flight path planning methods.
According to the flight path planning method, the device and the computer readable storage medium provided by the embodiment of the invention, when the flight path planning is carried out on the aircraft, the three-dimensional modeling is carried out on the physical space of the aircraft during the flight path planning, the starting point and the end point of the flight path to be planned are determined in the three-dimensional space environment model, the starting point is taken as the initial flight path planning node, then the calculation of the flight path optimization coefficient f (o) and the distance d (o) from the end point is carried out on the detection points on the circumference which takes the preset path search distance as the radius and takes the flight path planning node as the circle center, then the obstacle condition between each detection point and the end point is analyzed based on the calculation result, then the next round of path search is carried out on the flight path planning node again until the end point is searched, finally the planned flight path is determined according to the starting point, the newly planned flight path planning node and the end point, and based on, the method effectively reduces the calculation amount of the flight path planning, improves the flight path generation efficiency, and reduces the deviation between the planned flight path and the actual optimal flight path.
Other features and corresponding effects of the present invention are set forth in the following portions of the specification, and it should be understood that at least some of the effects are apparent from the description of the present invention.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic basic flow chart of a flight path planning method according to a first embodiment of the present invention;
FIG. 2 is a schematic diagram of a planar environment model according to a first embodiment of the present invention;
FIG. 3 is a schematic diagram of a three-dimensional environment model according to a first embodiment of the present invention;
fig. 4 is a schematic diagram of determining an obstacle coefficient of a track detection point according to a first embodiment of the present invention;
FIGS. 5a and 5b are schematic diagrams of a flight path planning provided by the second embodiment;
FIG. 6 is a schematic diagram of another route planning provided by the second embodiment;
fig. 7 is a schematic structural diagram of a flight path planning apparatus according to a third embodiment of the present invention;
fig. 8 is a schematic structural diagram of an electronic device according to a fourth embodiment of the invention.
Detailed Description
In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The first embodiment:
in order to solve the technical problems that when a route planning is performed by using an a-star algorithm and an artificial fish school algorithm in the related art, the efficiency of route generation is low, and a certain deviation exists between the generated route and an actual optimal route, the present embodiment provides a route planning method, and as shown in fig. 1, a basic flow diagram of the route planning method provided by the present embodiment is provided, and the route planning method provided by the present embodiment includes the following steps:
Specifically, the flight path planning method in this embodiment is an intelligent optimization algorithm that is inspired by plant growth characteristics, and the algorithm is based on plant behaviors and is a typical application of behavior definition in artificial intelligence. The basic idea is to search for the optimal solution in a search space by simulating the behaviors of phototaxis, auxin distribution and the like of plants. It should be understood that the aircraft in the present embodiment is applicable to any aircraft capable of moving in three-dimensional space, such as unmanned planes, airplanes, gliders, and the like.
It should be noted that the aircraft moves in a physical space, in order to implement the track planning, in this embodiment, an abstract space is obtained by performing environment modeling on a three-dimensional physical space during the flight of the aircraft, where the environment modeling is an important link of the track planning, and the purpose is to establish a three-dimensional space environment model that is convenient for the computer to perform the track planning, that is, to abstract an actual physical space (where the track is to be planned) into an abstract space that can be processed by an algorithm, so as to implement mapping between the abstract space and the abstract space. In practical applications, the three-dimensional physical space model may be generated according to a preset processing algorithm and a physical space where the flight path needs to be planned, where the processing algorithm includes, but is not limited to, a visual graph method, a tangent graph method, a Voronoi graph method, a topology method, a grid method, and the like.
Fig. 2 and 3 are schematic diagrams of environment models provided by the present embodiment, respectively, where fig. 2 is a schematic diagram of a planar environment model, fig. 3 is a schematic diagram of a three-dimensional environment, a center is an initial track planning node, a2, a3, and a4 in fig. 3 are re-planned track planning nodes, and from the initial point, a space is divided into hierarchical structures of different hierarchical spaces by a path with a length r each time, and the hierarchical structures are respectively a primary space, a secondary space, and a tertiary space (such as 1, 2, and 3 labeled in fig. 2 and 3) …, and so on. Discrete processing is carried out on the environment space, but the size of space division has direct influence on the size of environment information storage capacity and the length of planning time, the number of path segments is determined by the number of spatial division stages, and reasonably determining the value of r is an important link in environment model establishment.
Specifically, the aircraft is simulated as a plant bud tip in the embodiment, and the plant bud tip can be abstracted into an open self-organizing model with a plurality of search modes. The current growing point of the plant bud tip is represented by o, the corresponding illumination intensity is represented by f (o), the photosensitive range of the bud is a photosensitive aperture with r as the radius, r is the minimum unit of the growing speed in unit time, namely the moving distance of each time, and the length of a path section in each level of space circular ring in the constructed environment modeling space is r, so the value of r is reasonably determined. Based on this, in this embodiment, the track planning node of the aircraft corresponds to the growth point of the bud tip, the path search distance corresponds to the photosensitive radius of the bud tip, and the track optimization coefficient is used for the illumination intensity of the virtual bud tip. It should be understood that when m (o) of the track detection point on the circumference is equal to 0, f (o) is infinity, and is used for representing that the track detection point does not pass through the obstacle, otherwise, the track detection point passes through the obstacle.
in this embodiment, when all the track detection points on the circumference do not satisfy f (o) equal to ∞ and d (o) equal to 0, the newly planned track planning node is determined based on the current circumference in a manner that includes at least one of the following:
in the first mode, when all the track detection points on the circumference are the track detection points f (o) which are equal to ∞ and d (o) which are not equal to 0, the path search distance is increased to a new path search distance, and the current track planning node is determined as a newly planned track planning node.
Specifically, when the aircraft is simulated as the growth of the bud tip, the photosensitive aperture of the bud tip, that is, the track optimization coefficients of the track detection points on the circumference in the embodiment are all ∞, that is, m (o) of all the track detection points are equal to 0, the path search range is expanded, that is, the current track planning node is kept unchanged, and only the path search distance is increased, so that the obtained range of the circumference is expanded. In an implementation manner of this embodiment, when the path search distance is increased, a multiple increase manner may be adopted, for example, if the current path search distance is r, the subsequent path search distances may be located at 2r, 3r, and the like.
In an optional implementation manner of this embodiment, when the path search distance is increased to expand the path search range, the new path search distance satisfies any one of the following two conditions:
in the first condition, on a circle formed by taking a current track planning node as a circle center and a new path search distance as a radius, a track detection point f (o) which is not equal to ∞ and d (o) which is not equal to 0 begins to appear.
Specifically, in the current path search range, all track detection points on the circumference do not pass through the obstacle, and when the path search range is expanded, the expanded circumference is ensured to pass through the obstacle for the first time.
And secondly, on a circle formed by taking the current track planning node as the circle center and the new path searching distance as the radius, the maximum number of track detection points with f (o) not equal to ∞ and d (o) not equal to 0 appears.
Specifically, the present embodiment is different from the first condition, but after the expanded circumference passes through the obstacle for the first time, the path search range needs to be expanded continuously, whether the continuously expanded circumference passes through more track detection points of the obstacle is detected, and then in the process of expanding the path search range and searching for the obstacle, the radius of the circumference with the largest number of track detection points passing through the obstacle is determined as the new path search distance that needs to be expanded.
And secondly, when all the track detection points on the circumference comprise the track detection points f (o) which are not equal to infinity and d (o) which are not equal to 0, and f (o) which are equal to infinity and d (o) which are not equal to 0, determining d (o) values of all the track detection points f (o) which are equal to infinity and d (o) which are not equal to 0, and determining the track detection point with the minimum d (o) value as a newly planned track planning node.
Specifically, in this embodiment, if some points on the circumference pass through the obstacle and other points do not pass through the obstacle, the track detection point closest to the end point is selected from the track detection points that do not pass through the obstacle, and is used as the path planning point for performing the subsequent path search.
In an optional implementation manner of this embodiment, the specific determination manner of the value of d (o) is as follows: according to the formula
Respectively determining d (o) values of flight path detection points of which f (o) is equal to infinity and d (o) is not equal to 0; wherein the coordinates of the track detection point are represented as o (x)o,yo,zo) The coordinate of the end point is represented as C (x)c,yc,zc)。
In the third mode, when all the track detection points on the circumference include the track detection points f (o) not equal to ∞ and d (o) not equal to 0, and the track detection points f (o) not equal to ∞ and d (o) not equal to 0, based on the formula
And calculating f (o) values of all the flight path detection points of which f (o) is equal to infinity and d (o) is not equal to 0, and determining the flight path detection point with the maximum f (o) value as a newly planned flight path planning node.
In an optional implementation manner of this embodiment, calculating f (o) values of all track detection points based on the formula f (o) ═ 1/m (o) +1/d (o) includes: respectively making rays from each track detection point to an end point, and dividing the barrier into two parts through the rays; are respectively provided withCalculating the distance between the farthest point relative to the ray and the ray on the two parts, and determining the minimum value in the calculated distance as the value of m (o); according to the formula
Respectively determining d (o) values of each track detection point; wherein the coordinates of the track detection point are represented as o (x)o,yo,zo) The coordinate of the end point is represented as C (x)c,yc,zc) (ii) a And substituting the values of m (o) and d (o) into the formula f (o) 1/m (o) +1/d (o) to calculate the values of f (o) of all track detection points.
Specifically, assuming that the current flight path detection point to be calculated is o, the distance d (o) from the flight path detection point to the end point represents the current flight path detection point o (x)o,yo,zo) To the end point C (x)c,yc,zc) The calculation formula of the distance estimation value of (2) is:
as shown in fig. 4, a ray H is taken from the track detection point o to the end point C, the ray H divides an area from the point o to the point C in the virtual space into two parts (divided into an area p and an area q shown in fig. 4), distances H1 and H2 from the farthest points of the obstacle to the ray H in the two areas with respect to the ray H are calculated in the two areas p and q, respectively, and a value with a shorter distance is selected as an obstacle coefficient m (o), that is, m (o) ═ min (H1, H2). F (o) can be obtained by substituting the calculated d (o) and m (o) into the formula f (o) ═ 1/m (o) +1/d (o).
And 105, after the end point is detected through the circumference, determining a planned flight path in the three-dimensional space environment model according to the starting point, the newly planned flight path planning node and the end point.
Specifically, the path formed by the points searched by the algorithm is not necessarily a feasible path through which the aircraft can navigate, and further processing and smoothing are required to make the path become a practical feasible path.
In an optional implementation manner of this embodiment, determining a planned flight path in the three-dimensional space environment model according to the starting point, the newly planned flight path planning node, and the end point includes: connecting the starting point, the newly planned track planning node and the end point into a broken line; and smoothing the broken line to obtain a planned flight path in the three-dimensional space environment model.
According to the flight path planning method provided by the embodiment of the invention, when the flight path planning is carried out on the aircraft, the three-dimensional modeling is carried out on the physical space of the aircraft during the flight path planning, the starting point and the end point of the flight path to be planned are determined in the three-dimensional space environment model, the starting point is taken as the initial flight path planning node, then the calculation of the flight path optimization coefficient f (o) and the distance d (o) from the end point is carried out on the detection points on the circumference which takes the preset path search distance as the radius and takes the flight path planning node as the circle center, then the obstacle condition between each detection point and the end point is analyzed based on the calculation result, then the flight path planning node is re-planned to carry out the next round of path search until the end point is searched, finally the planned flight path is determined according to the starting point, the newly planned flight path planning node and the end point, and based on the implementation of the scheme of the application, the flight path generation efficiency is improved, and the deviation between the planned flight path and the actual optimal flight path is reduced.
Second embodiment:
in order to more intuitively understand the flight path planning method in the embodiment of the present invention, the second embodiment of the present invention describes the flight path planning method in detail with several specific examples.
As shown in fig. 5a and 5b, in an embodiment of the present embodiment, a starting point of a track to be planned is a1, an end point is C, first, a search is performed on a circle of a diaphragm with a radius of r from the starting point, since a point m (o) ≠ 0 (f) (o) ≠ infinity) is not found on the circle, which indicates that the current circle does not pass through an obstacle, the search is continued by keeping a1 as a center of the circle, forming a diaphragm with a radius of 2r, and when a part of the circle is found to be m (o) ≠ 0, a track detection point with m (o) ═ 0 and d (o) being the smallest is selected as a new track planning node from the diaphragm, that is, as shown in fig. 5a, the circle with a radius of 2r is selected as a new track planning nodeA2 and oaAll test points are m (o) ═ 0, and d (o) is relatively smaller, then d (o) of the test points and d (o) of the test points are compared, and the smaller one is selected to be a2 as a new route planning node.
Then, with a2 as a new track planning node, the search is continued from the circle of the aperture with r as the radius, and there is still an obstacle on the aperture (i.e. m (o) ≠ 0), and then the track detection point with m (o) ═ 0 and d (o) minimum is still selected as the new track planning node, i.e. as shown in fig. 5a, since a3 is the point on the aperture closest to the target point C, d (o) at a3 is minimum, and further a3 is used as the new track planning node.
Further, with a3 as a new track planning node, the search is continued from the circle of the aperture with r as the radius, and if there is still an obstacle on the aperture (i.e. m (o) ≠ 0), the test point with m (o) ═ 0 and d (o) minimum is still selected as a new point a, i.e. d (o) at a4 is minimum as shown in fig. 5a, and is used as a new track planning node.
Further, with a4 as a new path planning node, the search is continued from the circle of the aperture with r as the radius, most of the path detection points m (o) ≠ 0 (the path detection points on the circle of the aperture toward the target point C pass through the obstacle), and the direction from these path detection points o to C is
The ray h and the ray h divide the area from the track detection point to the point C into two, the distance from the farthest point of the obstacle to the ray h is calculated in the p area and the q area respectively, the value with the shortest distance is selected as m (o), namely m (o) min (h1, h2), m (o) can be obtained from each test point o, the track optimization coefficient of each track detection point is calculated at the moment, the point with the largest track optimization coefficient is selected as a new track planning node according to the formula f (o) 1/m (o) +1/d (o), for example, as shown in fig. 5a, the comparison track detection point o is compared with the point o1And o2Intensity of light at o2F (o) is larger, and becomes the new trajectory planning node a 5.
Further, with a5 as a new track planning node, the search is continued from the circle of the aperture with r as the radius, and if there is still an obstacle on the aperture (i.e. m (o) ≠ 0), the test point with m (o) ═ 0 and d (o) minimum is still selected as the new track planning node, i.e. as shown in fig. 5b, d (o) at a6 is minimum, and is the new track planning node.
And taking a6 as a new path planning node, continuing searching from the circle of the aperture with the radius of r, wherein no obstacle exists on the aperture, all path detection points are m (o) equal to 0, the radius of the aperture is multiplied, when searching with the aperture with the radius of fr, finding the path detection points with m (o) equal to 0 and d (o) infinitely close to 0, then reaching a point C, and ending the searching, wherein a broken line formed by connecting a1, a2, a3, a4, a5, a6 and C is the planned path, which is specifically shown in fig. 5 b.
As shown in fig. 6, in another embodiment of the present embodiment, a starting point of a flight path to be planned is a1, an end point is C, first, a point m (o) ≠ 0 (f) (o) ≠ infinity) is found on the circle of the iris starting from the starting point, which means that the current circle does not pass through the obstacle, when the circle is found, the search is continued by keeping a1 as the center of the circle and forming the iris with 2r as the radius, when a part m (o) () ≠ 0 is found on the circle, that is, the obstacle is found, but at this time, the path search distance is still increased, the obstacle is continued by forming the iris with a larger radius, however, when the search is performed with 3r as the radius, the circle of the iris no longer passes through the obstacle, and thus, the path search range formed by the circle with 2r as the radius is the proper range, therefore, the new path planning node is selected from the circle of the aperture with the radius of 2r, where m (o) is 0 and d (o) is the smallest path detection point, that is, as shown in fig. 6, on the circle with the radius of 2r, a2 and oaAll test points are m (o) ═ 0, and d (o) is relatively smaller, then d (o) of the test points and d (o) of the test points are compared, and the smaller one is selected to be a2 as a new route planning node.
Then, with a2 as a new track planning node, the search is continued from the circle of the aperture with r as the radius, in the process of searching the obstacles with r and 2r as the radius respectively, another obstacle is found, the aperture range is expanded until the obstacle is searched, and then the point with m (o) being 0 and d (o) being the minimum is found on the aperture with 3r as the radius, namely the point a 3.
Further, taking a3 point as a new track planning node, performing search selection on the circle of the aperture with r as the radius, where there is no obstacle on the aperture, and all track detection points are m (o) 0, the aperture radius is multiplied, when searching with the aperture with radius fr, finding the test point o where m (o) 0 and d (o) are infinitely close to 0, then proceeding to o and ending, reaching C point, and ending the search, where the broken line formed by connecting a1, a2, a3, and C is the planned track, please refer to fig. 6 specifically.
In the two embodiments, in the former embodiment, the path search distance is increased to search for an obstacle only when m (o) of all the track detection points on the circumference is 0, and in the latter embodiment, the path search distance is increased after the obstacle is searched until the number of track detection points passing through the obstacle on the formed circumference is as large as possible. It should be noted that the track length calculated in the former embodiment is longer than that in the latter embodiment, but in the algorithm execution process, the algorithm complexity is relatively low, the calculation speed is relatively high, the algorithm time consumption is greatly reduced, and the method is suitable for real-time track planning in the dynamic flight process of the aircraft, namely, in unknown and complex environments and in scenes with high real-time requirements on flight; the latter embodiment searches in advance, analyzes the environment, has long time consumption and optimal path, and is suitable for the aircraft with strong detection capability, simple and fixed surrounding environment information and no high requirement on real-time performance.
The third embodiment:
in order to solve the technical problems that when a route planning is performed by using an a-star algorithm and an artificial fish swarm algorithm in the related art, the efficiency of route generation is low, and a certain deviation exists between the generated route and an actual optimal route, this embodiment shows a route planning device, and specifically please refer to fig. 7, the route planning device of this embodiment includes:
the model building module 701 is used for building a three-dimensional space environment model based on a physical space of the aircraft during navigation, and determining a starting point and an end point of a flight path to be planned on the three-dimensional space environment model; the starting point is an initial track planning node;
a calculating module 702, configured to use a target point on a circumference formed by taking a track planning node as a circle center and a preset path search distance as a radius as a track detection point, and perform calculation of f (o) and d (o) on all the track detection points; wherein, o is the mark of the track detection point, f (o) is the track optimization coefficient, f (o) is related to d (o) and m (o), m (o) is the barrier coefficient, when m (o) is 0, the characteristic path test point does not pass through the barrier, when m (o) is not equal to 0, the characteristic path test point passes through the barrier, d (o) is the straight line distance between the track detection point and the terminal point;
a planning module 703 for determining a target track detection point as an end point when there is a target track detection point on the circumference where f (o) is equal to ∞ and d (o) is equal to 0; when all the track detection points on the circumference do not satisfy f (o) equal to ∞ and d (o) equal to 0, determining a newly planned track planning node, and inputting the newly planned track planning node to the calculation module 702 to make the calculation module 702 continue to execute its function;
and a route determining module 704, configured to determine a planned route in the three-dimensional space environment model according to the starting point, the newly planned route planning node, and the end point after the end point is detected through the circumference.
Specifically, the flight path planning method in this embodiment is an intelligent optimization algorithm that is inspired by plant growth characteristics, and the algorithm is based on plant behaviors and is a typical application of behavior definition in artificial intelligence. The basic idea is to search for the optimal solution in a search space by simulating the behaviors of phototaxis, auxin distribution and the like of plants. The aircraft is simulated as a plant bud tip in the embodiment, and the plant bud tip can be abstracted into an open self-organizing model with a plurality of search modes. The current growing point of the plant bud tip is represented by o, the corresponding illumination intensity is represented by f (o), the photosensitive range of the bud is a photosensitive aperture with r as a radius, and r is the minimum unit of the growing speed in unit time, namely the moving distance of each time. Based on this, in this embodiment, the track planning node of the aircraft corresponds to the growth point of the bud tip, the path search distance corresponds to the radius of the photosensitive aperture of the bud tip, and the track optimization coefficient is used for the illumination intensity of the virtual bud tip. It should be understood that when m (o) of the track detection point on the circumference is equal to 0, f (o) is infinity, and is used for representing that the track detection point does not pass through the obstacle, otherwise, the track detection point passes through the obstacle.
In the present embodiment, when all the track detection points on the circumference do not satisfy f (o) equal to ∞ and d (o) equal to 0, the newly planned track planning node is determined based on the current circumference and continuously input to the calculation module 702 to continuously perform the correlation calculation.
In some embodiments of this embodiment, the planning module 703 is specifically configured to perform at least one of the following: when all the track detection points on the circumference are f (o) equal to infinity and d (o) not equal to 0, increasing the path search distance to a new path search distance, and determining the current track planning node as a newly planned track planning node; when all the track detection points on the circumference comprise f (o) track detection points which are not equal to infinity and d (o) are not equal to 0, and f (o) track detection points which are equal to infinity and d (o) are not equal to 0, determining d (o) values of all the track detection points which are f (o) equal to infinity and d (o) are not equal to 0, and determining the track detection point with the minimum d (o) value as a newly planned track planning node; when all the track detection points on the circumference comprise the track detection points f (o) which are not equal to infinity and d (o) which are not equal to 0, and the track detection points f (o) which are equal to infinity and d (o) which are not equal to 0, calculating f (o) values of all the track detection points f (o) which are equal to infinity and d (o) which are not equal to 0 based on the formula f (o) 1/m (o) +1/d (o), and determining the track detection point f (o) with the largest value as a newly planned track planning node.
Further, in some implementations of this embodiment, the new path search distance satisfies the following condition: starting to present f (o) track detection points which are not equal to infinity and d (o) are not equal to 0 on a circle formed by taking the current track planning node as the circle center and the new path searching distance as the radius; or, on a circle formed by taking the current track planning node as the center of circle and the new path searching distance as the radius, the number of the track detection points which appear f (o) is not equal to ∞ and d (o) is not equal to 0 is the largest.
In some embodiments of this embodiment, the planning module 703 is specifically configured to generate the formula
Respectively determining d (o) values of flight path detection points of which f (o) is equal to infinity and d (o) is not equal to 0; wherein the coordinates of the track detection point are represented as o (x)o,yo,zo) The coordinate of the end point is represented as C (x)c,yc,zc)。
In other embodiments of this embodiment, the planning module 703 is further configured to separately perform a ray on each track detection point toward the end point, and divide the obstacle into two parts by using the ray; respectively calculating the distances from the farthest points relative to the ray on the two parts, and determining the minimum value in the calculated distances as an m (o) value; according to the formula
Respectively determining d (o) values of each track detection point; wherein the coordinates of the track detection point are represented as o (x)o,yo,zo) The coordinate of the end point is represented as C (x)c,yc,zc) (ii) a And substituting the values of m (o) and d (o) into the formula f (o) 1/m (o) +1/d (o) to calculate the values of f (o) of all track detection points.
In some embodiments of this embodiment, the track determining module 704 is specifically configured to connect the starting point, the newly planned track planning node, and the ending point into a broken line; and smoothing the broken line to obtain a planned flight path in the three-dimensional space environment model.
It should be noted that, the flight path planning method in the foregoing embodiments can be implemented based on the flight path planning device provided in this embodiment, and it can be clearly understood by those skilled in the art that, for convenience and simplicity of description, the specific working process of the flight path planning device described in this embodiment may refer to the corresponding process in the foregoing method embodiments, and details are not described here.
By adopting the flight path planning device provided by the embodiment, when the flight path planning is carried out on the aircraft, the physical space of the aircraft during the flight path is firstly subjected to three-dimensional modeling, the starting point and the end point of the flight path to be planned are determined in a three-dimensional space environment model, the starting point is taken as an initial flight path planning node, then the calculation of a flight path optimization coefficient f (o) and the distance d (o) from the end point is carried out on the detection points on the circumference which takes the preset path searching distance as the radius and takes the flight path planning node as the circle center, then the obstacle condition between each detection point and the end point is analyzed based on the calculation result, then the flight path planning node is re-planned to carry out the next round of path searching until the end point is searched, and finally the planned flight path is determined according to the starting point, the newly planned flight path planning node and the end point, and based on the implementation of the scheme of the application, the flight path generation efficiency is improved, and the deviation between the planned flight path and the actual optimal flight path is reduced.
The fourth embodiment:
the present embodiment provides an electronic device, as shown in fig. 8, which includes a processor 801, a memory 802, and a communication bus 803, wherein: the communication bus 803 is used for realizing connection communication between the processor 801 and the memory 802; the processor 801 is configured to execute one or more computer programs stored in the memory 802 to implement at least one step of the flight path planning method of the foregoing embodiments.
The present embodiments also provide a computer-readable storage medium including volatile or non-volatile, removable or non-removable media implemented in any method or technology for storage of information such as computer-readable instructions, data structures, computer program modules or other data. Computer-readable storage media include, but are not limited to, RAM (Random Access Memory), ROM (Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), flash Memory or other Memory technology, CD-ROM (Compact disk Read-Only Memory), Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can be accessed by a computer.
The computer-readable storage medium in this embodiment may be used to store one or more computer programs, which stored one or more computer programs may be executed by a processor to implement at least one step of the flight path planning method of the foregoing embodiment.
The present embodiment also provides a computer program, which can be distributed on a computer readable medium and executed by a computing device to implement at least one step of the flight path planning method of the foregoing embodiment; and in some cases at least one of the steps shown or described may be performed in an order different than that described in the embodiments above.
The present embodiments also provide a computer program product comprising a computer readable means on which a computer program as shown above is stored. The computer readable means in this embodiment may include a computer readable storage medium as shown above.
It will be apparent to those skilled in the art that all or some of the steps of the methods, systems, functional modules/units in the devices disclosed above may be implemented as software (which may be implemented in computer program code executable by a computing device), firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed by several physical components in cooperation. Some or all of the physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit.
In addition, communication media typically embodies computer readable instructions, data structures, computer program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to one of ordinary skill in the art. Thus, the present invention is not limited to any specific combination of hardware and software.
The foregoing is a more detailed description of embodiments of the present invention, and the present invention is not to be considered limited to such descriptions. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all shall be considered as belonging to the protection scope of the invention.
Claims (10)
1. A method of flight path planning, comprising:
a, constructing a three-dimensional space environment model based on a physical space of an aircraft during navigation, and determining a starting point and an end point of a flight path to be planned on the three-dimensional space environment model; the starting point is an initial track planning node;
step B, taking a target point on a circumference formed by taking a track planning node as a circle center and a preset path searching distance as a radius as a track detection point, and calculating f (o) and d (o) of all the track detection points; wherein o is the mark of the track detection point, f (o) is the track optimization coefficient,
m (o) is an obstacle coefficient, when m (o) is equal to 0, a path test point is characterized not to pass through an obstacle, when m (o) is equal to 0, the path test point is characterized to pass through the obstacle, and d (o) is a straight-line distance between the track detection point and the terminal point;
step C, when a target track detection point with f (o) equal to infinity and d (o) equal to 0 exists on the circumference, determining the target track detection point as the end point; when all the track detection points on the circumference do not meet f (o) is equal to infinity and d (o) is equal to 0, determining a newly planned track planning node and returning to execute the step B;
and D, after the end point is detected through the circumference, determining a planned flight path in the three-dimensional space environment model according to the starting point, the newly planned flight path planning node and the end point.
2. The trajectory planning method according to claim 1, wherein, when f (o) is equal to ∞ and d (o) is equal to 0, none of the trajectory detection points on the circle is satisfied, determining a newly planned trajectory planning node includes at least one of:
when all the track detection points on the circumference are the track detection points f (o) is equal to ∞ and d (o) is not equal to 0, increasing the path search distance to a new path search distance, and determining the current track planning node as a newly planned track planning node;
when the f (o) is not equal to infinity and the d (o) is not equal to 0, and f (o) is equal to infinity and the d (o) is not equal to 0, all the d (o) values of the f (o) is equal to infinity and the d (o) is not equal to 0 are determined, and the path detection point with the minimum d (o) value is determined as a newly planned path planning node.
3. The trajectory planning method according to claim 2, wherein the new path search distance satisfies the following condition:
starting to present a track detection point f (o) which is not equal to ∞ and d (o) which is not equal to 0 on a circle formed by taking the current track planning node as a circle center and the new path searching distance as a radius;
or, on a circle formed by taking the current track planning node as a circle center and the new path searching distance as a radius, the number of track detection points which appear f (o) is not equal to ∞ and d (o) is not equal to 0 is the largest.
4. The trajectory planning method of claim 2, wherein said determining d (o) values for all of said flight path detection points where f (o) is equal to ∞ and d (o) is not equal to 0 comprises:
according to the formula
Respectively determining d (o) values of the flight path detection points of which f (o) is equal to infinity and d (o) is not equal to 0; wherein the coordinates of the track detection point are represented as o (x)o,yo,zo) The coordinate of the end point is represented as C (x)c,yc,zc)。
5. The trajectory planning method of claim 1, wherein said determining a planned trajectory in the three-dimensional spatial environment model based on the starting point, the newly planned trajectory planning node, and the ending point comprises:
connecting the starting point, the newly planned route planning node and the terminal point into a broken line;
and smoothing the broken line to obtain a planned flight path in the three-dimensional space environment model.
6. A trajectory planning device, comprising:
the model building module is used for building a three-dimensional space environment model based on a physical space of an aircraft during navigation and determining a starting point and an end point of a flight path to be planned on the three-dimensional space environment model; the starting point is an initial track planning node;
the calculation module is used for taking a target point on a circumference formed by taking a track planning node as a circle center and a preset path search distance as a radius as a track detection point and calculating f (o) and d (o) of all the track detection points; wherein o is the mark of the track detection point, f (o) is the track optimization coefficient,
m (o) is an obstacle coefficient, when m (o) is equal to 0, the path test points are characterized not to pass through the obstacle, when m (o) is equal to 0, the path test points are characterized to pass through the obstacle, and d (o) is the straight line between the track detection point and the end pointA line distance;
a planning module for determining a target track detection point as the end point when the target track detection point of f (o) equal to ∞ and d (o) equal to 0 exists on the circumference; when all the track detection points on the circumference do not satisfy f (o) is equal to ∞ and d (o) is equal to 0, determining a newly planned track planning node and inputting the newly planned track planning node to the calculation module to cause the calculation module to continue to execute its function;
and the route determining module is used for determining a planned route in the three-dimensional space environment model according to the starting point, the newly planned route planning node and the end point after the end point is detected through the circumference.
7. The trajectory planning device of claim 6, wherein the planning module is specifically configured to perform at least one of:
when all the track detection points on the circumference are the track detection points f (o) is equal to ∞ and d (o) is not equal to 0, increasing the path search distance to a new path search distance, and determining the current track planning node as a newly planned track planning node;
when the f (o) is not equal to infinity and the d (o) is not equal to 0, and f (o) is equal to infinity and the d (o) is not equal to 0, all the d (o) values of the f (o) is equal to infinity and the d (o) is not equal to 0 are determined, and the path detection point with the minimum d (o) value is determined as a newly planned path planning node.
8. The trajectory planner of claim 7 wherein the new path search distance satisfies the following condition:
starting to present a track detection point f (o) which is not equal to ∞ and d (o) which is not equal to 0 on a circle formed by taking the current track planning node as a circle center and the new path searching distance as a radius;
or, on a circle formed by taking the current track planning node as a circle center and the new path searching distance as a radius, the number of track detection points which appear f (o) is not equal to ∞ and d (o) is not equal to 0 is the largest.
9. An electronic device, comprising: a processor, a memory, and a communication bus;
the communication bus is used for realizing connection communication between the processor and the memory;
the processor is configured to execute one or more programs stored in the memory to implement the steps of the flight path planning method according to any one of claims 1 to 5.
10. A computer readable storage medium, characterized in that the computer readable storage medium stores one or more programs which are executable by one or more processors to implement the steps of the flight path planning method according to any one of claims 1 to 5.
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